ArticleBMC proceedings2009
Comparison of analyses of the QTLMAS XII common dataset. II: genome-wide association and fine mapping.
Article in BMC proceedings, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- An Efficient Genome-Wide Multilocus Epistasis Search.Genetics · 2015Article
- Why breeding values estimated using familial data should not be used for genome-wide association studies.G3 (Bethesda, Md.) · 2014Article
- Impact of prior specifications in a shrinkage-inducing Bayesian model for quantitative trait mapping and genomic prediction.Genetics, selection, evolution : GSE · 2013Article
- Overview of LASSO-related penalized regression methods for quantitative trait mapping and genomic selection.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012Review
- Allele coding in genomic evaluation.Genetics, selection, evolution : GSE · 2011Article
- Local genealogies in a linear mixed model for genome-wide association mapping in complex pedigreed populations.PloS one · 2011Article
- Genomic selection and complex trait prediction using a fast EM algorithm applied to genome-wide markers.BMC bioinformatics · 2010Article
- A genetic algorithm based method for stringent haplotyping of family data.BMC genetics · 2009Article
- Article
- A Bayesian QTL linkage analysis of the common dataset from the 12th QTLMAS workshop.BMC proceedings · 2009Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
As part of the QTLMAS XII workshop, a simulated dataset was distributed and participants were invited to submit analyses of the data based on genome-wide association, fine mapping and genomic selection. We have evaluated the findings from the groups that reported fine mapping and genome-wide association (GWA) efforts to map quantitative trait loci (QTL). Generally the power to detect QTL was high and the Type 1 error was low. Estimates of QTL locations were generally very accurate. Some methods were much better than others at estimating QTL effects, and with some the accuracy depended on simulated effect size or minor allele frequency. There were also indications of bias in the effect estimates. No epistasis was simulated, but the two studies that included searches for epistasis reported several interacting loci, indicating a problem with controlling the Type I error rate in these analyses. Although this study is based on a single dataset, it indicates that there is a need to improve fine mapping and GWA methods with respect to estimation of genetic effects, appropriate choice of significance thresholds and analysis of epistasis.
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Registered trials
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